Prospect identification seeks to accurately develop a list of prospective business clients that fit a broker's interest in insurance products and industries (i.e., the broker's “appetite”). Brokers typically have a current list of clients that defines their appetite, and they typically wish to find other similar companies. The overall objective of the prospect identification development is to enhance and automate several aspects of client prospect identification, discovery, and analysis using a combination of machine learning, natural language processing, mathematical modeling, and relational database modeling. By doing so, prospect results are provided more efficiently and at a higher quality.
Currently, prospecting is done on an ad-hoc basis, with brokers and account executives discovering prospects through word of mouth, industry publications, etc. Information must be manually gleaned through extensive searching and analysis, and all this information is tracked in spreadsheets, lists, and other disjointed databases. Only once a prospective client's business model and corporate attributes have been analyzed can a broker then decide whether to pursue the prospective client's business. Extensive man-hours are required to generate this information, and extensive man-hours are required to keep this information updated. Even then, due to inconsistencies in company names that exist throughout various data sources (e.g., multiple variants, incorrect spelling, subsidiaries and divisions, etc.), a broker may end up pursuing a prospect with which the broker already has an existing relationship. Existing customer relationship management software tools take blanket approaches that do not account for the brokers' or account executives' interests and do not account for the above-described problems with company name inconsistencies and nuances.
The inventors sought to develop a software-based automated tool to develop an understanding of a given broker's specific appetite and return, in real-time, a list of prospects that meet this appetite, including actionable information for deciding whether to pursue the prospect. In this way, a broker can instantly use this real-time information to make a decision on the viability of a prospect. Further, the inventors sought to perform client/company matching to alleviate the issues surrounding multiple name variants, corporate hierarchies, and incorrect spelling, which thus enables the broker to readily determine whether the broker already has an existing business relationship with the prospect or if there is some preexisting relationship (e.g., at a hierarchical level) that can be leveraged in engaging the new prospect.